人工智能技术在细菌学中的应用的图书统计分析:一个PRISMA引导的研究议程
Diana Carolina Velasco Cardona1, Sebastián Cardona-Acevedo2, Alejandro Valencia-Arias3
1Ciencias de la Salud, Institución Universitaria Colegio Mayor de Antioquia, Medellín, Colombia.
Frontiers in microbiology
|October 2, 2025
概括
细菌学中的人工智能 (AI) 正在快速增长,最近细菌分类和诊断方面取得了进展. 未来的研究应该专注于先进的AI方法,如深度学习,以解决现有的差距.
科学领域:
- 微生物学 微生物学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 人工智能 (AI) 的整合使得大规模微生物数据集的分析成为可能.
- 显著的研究差距阻碍了人工智能在细菌研究和诊断方面的全部潜力.
研究的目的:
- 分析全球科学生产的AI应用在细菌学.
- 根据图书识别趋势提出未来的研究议程.
主要方法:
- 以PRISMA 2020框架为指导的图书统计分析.
- 从Scopus和科学网络中检索元数据.
- 使用了定量指标,并发网络和主题映射.
主要成果:
- 从2022年到2024年,科学成果的指数式增长.
- 美国和中国是最大的生产国.
- 主题演变显示了向细菌分类,诊断和新兴术语如"元基因组学"和"转移学习"的转变.
结论:
- 细菌学中的AI正在扩大,但依赖于传统方法.
- 需要整合先进的AI,如深度学习和变压器模型.
- 这些发现支持跨学科合作和创新的议程.
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